What best predicts computer proficiency?

ABSTRACT

Identifying variables that predict computer aptitude can help educators and employers target potential students and employees. The authors examine a number of possible explanatory variables including demographic profiles, high school achievements, prior computer training and experience, cognitive styles, and problem-solving abilities.

REFERENCES

• 1: Alspaugh, C.A. Identification of some components of computer programming aptitude. J. Research in Mathematics Education 3, 2 (Mar. 1972), 89-98.
• 2: Bateman, C.R. Predicting performance in a basic computer course. In Proceedings of the 5th Annual Meeting of the American Institute for Decision Sciences AIDS Press, Atlanta, GA, 1973.
• 3: Briggs, K.C., and Myers, I.B. Myers-Briggs type indicator, abbreviated version. Consulting Psychologists Press, Inc., Palo Alto, CA.
• 4: D. F. Butcher , W. A. Muth, Predicting performance in an introductory computer science course, Communications of the ACM, v.28 n.3, p.263-268, March 1985 [doi>10.1145/3166.3167]
• 5: Patricia F. Campbell , George P. McCabe, Predicting the success of freshmen in a computer science major, Communications of the ACM, v.27 n.11, p.1108-1113, Nov. 1984 [doi>10.1145/1968.358288]
• 6: C. K. Capstick , J. D. Gordon , A. Salvadori, Predicting performance by university students in introductory computing courses, ACM SIGCSE Bulletin, v.7 n.3, p.21-29, Sept. 1975 [doi>10.1145/382216.382483]
• 7: T. P. Cronan , P. R. Embry , S. D. White, Identifying factors that influence performance of non-computing majors in the business computer information systems course, Journal of Research on Computing in Education, v.21 n.4, p.431-446, June 1989
• 8: Deckro, R.F., and Woundenberg, H.W. MBA admission criteria and academic success, Decision Sciences {Oct. 1977), 765-799.
• 9: Denelsky, G.Y., and McKee, M.G. Prediction of computer programmer training and job performance using the AABP test. Personal Psychology (1974), 129-137.
• 10: Evans, G.E. Learning to program computers by learning to solve problems. J. Education for Business 64, 2, 77-79.
• 11: Evans, G.E., and Simkin, M.G. Student backgrounds and computer abilities: How closely are they related? Proceedings of the Western Regional Conference of the Data Processing Management Association (Reno, Nev., Sept. 1987), pp. 1-6.
• 12: Fowler, G.E., and Glorfeld, L.W. Predicting aptitude in introductory computing: A classification model. AEDS J. 14, 2 (Winter I981}, 96- 109.
• 13: Louis W. Glorfeld , George C. Fowler, Validation of a model for predicting aptitude for introductory computing, Proceedings of the thirteenth SIGCSE technical symposium on Computer science education, p.140-143, February 11-12, 1982, Indianapolis, Indiana, United States
• 14: Hostetler, T.R. Predicting student success in an introductory programming course. In Proceedings of NECC5, IEEE Press, Silver Spring, MD, 1983.
• 15: Konvalina, J., Stephens, L., and Wileman, S. Identifying factors influencing computer science aptitude and achievement. AEDS J. 16, 2 (Winter 1983), 106-112.
• 16: Richard E. Mayer , Jennifer L. Dyck , William Vilberg, Learning to program and learning to think: what's the connection?, Communications of the ACM, v.29 n.7, p.605-610, July 1986 [doi>10.1145/6138.6142]
• 17: Lawrence J. Mazlack, Identifying potential to acquire programming skill, Communications of the ACM, v.23 n.1, p.14-17, Jan. 1980 [doi>10.1145/358808.358811]
• 18: Petersen, C.C., and Howe, T.G. Predicting academic success in introduction to computers AEDS J. (Summer 1979), 182-191.
• 19: Stevens, D.J. Cognitive processes and success of students in instructional computer courses. AEDS J. (Summer 1983), 228-233.
• 20: Stevens, L.J., Wileman, S., and Konvalina, J. Group differences in computer aptitude. AEDS J. (Winter 1981), 84-95.
• 21: Webb, N.M. Microcomputer learning in small groups: Cognitive requirements and group processes. J. Educational Psychology 76 6 (Dec. 1984), 1076-1088.
• 22: Kathy Brittain White , Richard Leifer, Information systems development success: Perspectives from project team participants, MIS Quarterly, v.10 n.3, p.215-223, Sept. 1986 [doi>10.2307/249253]

INDEX TERMS

Primary Classification:
  K. Computing Milieux
  K.3 COMPUTERS AND EDUCATION

Additional Classification:
  J. Computer Applications
  J.1 ADMINISTRATIVE DATA PROCESSING
      Subjects: Education

  K. Computing Milieux
  K.7 THE COMPUTING PROFESSION

General Terms:
Human Factors, Measurement